Device and method for computation of channel loss rate and collision loss rate of communication link(s) in a random access network

ABSTRACT

A method is intended for computing online channel loss rate and collision loss rate of at least one communication link established between nodes of a network using a random access MAC protocol. This method comprises the steps of i) dividing time in probing windows and transmitting a chosen number S of probe packets during each probing window from a transmitter node to a receiver node linked therebetween, ii) measuring a packet loss rate from probe packets lost on this communication link during a probing window, iii) scanning each probing window with smaller sliding windows, each having a size Wk smaller than S, to identify the sliding window during which only channel losses occur, and then for computing a channel loss rate on this communication link from this identified sliding window, and iv) computing a collision loss rate on this communication link by subtracting the computed channel loss rate from the measured packet loss rate.

This application claims the benefit, under 35 U.S.C. §365 ofInternational Application PCT/EP2010/053640, filed Mar. 19, 2010, whichwas published in accordance with PCT Article 21(2) on Nov. 4, 2010 inEnglish and which claims the benefit of European patent application No.09305366.8, filed Apr. 28, 2009.

TECHNICAL FIELD

The present invention relates to random access networks, and moreprecisely to packet loss computation during operation in such networks.

One means here by “random access network” a network in which nodesoperate based on a random access (or “contention-based”) MAC (“MediumAccess Control”) protocol, such as ALOHA or CSMA (“Carrier SenseMultiple Access”), for instance. So it could be a fixed (communication)network or a wireless (communication) network, and notably an IEEE802.11 network (i.e. a WLAN (Wireless Local Area Network), for instanceof the WiFi type), or an IEEE 802.15.4 network (or ZigBee), or else asatellite network. It is recalled that in ALOHA MAC protocols nodescontend for the medium only using random backoff, while in CSMA MACprotocols nodes in addition use carrier sensing before performing randombackoff.

BACKGROUND OF THE INVENTION

As it is known by the man skilled in the art, during operation in arandom access network packet losses can be either due to channel errorsor due to collisions.

One means here by “collision losses” packet losses that occur when twoor more packets arrive simultaneously (or “collide”) at a receiver node.

Moreover one means here by “channel error losses” packet losses that donot involve simultaneous packet transmissions and that are due to the(wireless) channel (or link) between a transmitter node and a receivernode. It is recalled that the (wireless) channel behavior dependsnotably on node locations and/or transmit power and/or received signalstrength and/or (wireless) hardware implementation and/or environmentalfactors.

Packet loss rate during network operation can be measured by means ofgroups of probe packets transmitted between nodes during pre-specifiedprobing time windows. In this case, the packet loss rate is the fractionof probe packets that have been lost during a pre-specified probing timewindow. Unfortunately it is much more difficult to separate (or compute)the two components of the measured packet loss rate, i.e. the channelloss rate and the collision loss rate, during the operation of a randomaccess network, whereas it is of interest for the two following reasons.

Firstly, this separation enables efficient joint operation of randomaccess MAC protocols and data rate adaptation mechanisms. It is recalledthat random access protocols and data rate adaptation mechanisms aim ataddressing different causes of packet loss. Random access MAC protocolsaim to address losses due to collisions by carrier sensing andcontention window adaptation, while data rate adaptation mechanisms aimto improve channel quality on an individual link by adapting themodulation data rate. Both random access MAC protocols and data rateadaptation mechanisms trade off throughput efficiency for packet lossavoidance, but they both require knowledge of the cause of packet lossfor correct operation. Unfortunately, this information is not providedby the physical (PHY) layer specifications of existing (wireless)standards. So, all random access MAC protocols assume that a packet lossis due to collisions and therefore increase the contention window size(in case of CSMA/CA) or the backoff probability (in case of ALOHA), andall data rate adaptation mechanisms assume that a packet loss is due topoor channel quality and therefore decrease the modulation data rate tolower the bit error probability by increasing the transmit poweravailable to each bit. Therefore, unless these mechanisms can correctlyascertain the causes of packet losses, they may take unnecessary orerroneous actions that result in inefficient operation.

Secondly, this separation enables accurate capacity estimation, trafficoptimizations and admission control in random access networks. Incontrast to networks using scheduled access MAC protocols, such as TimeDivision Multiple Access (TDMA), it is well known by the man skilled inthe art that it is hard to model and optimize networks using randomaccess MAC protocols. Traffic optimizations require measurement of atraffic-independent network state (link capacity) to optimally allocatetraffic to available resources. Accurately estimating thistraffic-independent network state calls for measuring link capacities inthe absence of collisions, as these collisions may only arise oncetraffic has been allocated in the network. Separation of collisionlosses (traffic-dependent) and channel error losses (trafficindependent) is, therefore, crucial for properly sizing link capacitiesso as to be able to allocate traffic to optimize the performance ofrandom access networks.

Solutions which have been proposed to separate channel losses fromcollision losses can be approximately shared in two classes: a two-phaseclass and a continuous class. In a two-phase class solution the networkperiodically suspends operation to measure channel loss rates, while ina continuous class solution the network operation is never suspended.

More precisely, a two-phase class solution is based on the division ofthe time of network operation in two phases: a measurement phase and anormal network operation phase. During the measurement phase, normalnetwork operation is suspended and the nodes must execute a sequentialtransmission technique to broadcast probe packets sequentially in ascheduled manner. Since only one node transmits at a time, this solutioncan measure the channel loss rates of all communication links in thenetwork during this probing window, using O(N) measurements, where N isthe number of nodes in the network. Then, the collision rate for thisprobing window is extracted from the measured packet loss rate of thesubsequent normal network operation phase.

Unfortunately these two-phases class solutions seem impractical and notapplicable to an operational network. Indeed, they impose an extendednetwork downtime just for network measurements. In order to collectsufficient statistics, each node needs to transmit for tens of secondsduring the measurement phase, as mentioned in the document of JitendraPadhye et al., “Estimation of Link Interference in Static Multi-hopWireless Networks”, Proceedings of Internet Measurement Conference,Berkeley, Calif., October 2005, or in the document of Lili Qiu et al.,“A general model of wireless interference”, Proceedings of InternationalConference on Mobile Computing and Networking, Montréal, Canada,September 2007, or in the document of Anand Kashyap et al., “Ameasurement-based approach to modeling link capacity in 802.11-basedwireless networks”, Proceedings of International Conference on MobileComputing and Networking, Montreal, Canada, September 2007, or else inthe document of Charles Reis et al., “Measurement-based models ofdelivery and interference in static wireless networks”, Proceedings ofthe 2006 conference on Applications, technologies, architectures, andprotocols for computer communications, Pisa, Italy, September 2006.Thus, each measurement phase can result in network downtime of severalminutes even for small networks of 20-30 nodes.

Moreover, the implementation of the sequential technique in anoperational network requires a signaling protocol to coordinate thenodes so that they could be able to switch between the two phases. Thissignaling protocol is itself a source of overhead and is difficult toimplement in general network environments (multi-hop or distributed, forinstance).

The continuous class comprises per-packet solutions that attempt todetect the cause of packet loss for each transmitted packet, and passivemonitoring techniques where additional monitoring devices “sniff”received packets and send packet timing information to a centralizedpoint which is in charge of estimating the loss rates using globalinformation.

A first solution of the continuous class is described in the document ofS. Rayanchu et al., “Diagnosing Wireless Packet Losses in 802.11:Separating Collision from Weak Signal”, IEEE INFOCOM 2006, Barcelona,Spain. This first solution attempts to diagnose the cause of loss on aper-packet basis in 802.11 WLANs, that are single-hop networksconsisting of clients connected to an access point (AP). For each packettransmitted by a client and received in error at an access point, thelatter acknowledges with a copy of this erroneous packet. Then, theclient uses statistical techniques to determine whether the packet wascorrupted due to collisions or channel losses. This technique can beused to estimate channel loss rate and collision loss rate by countingthe fractions of corrupted packets due to channel errors during apre-specified time window.

This first solution has several drawbacks. Firstly, it introducesoverhead due to the additional acknowledgment packets (and this overheadis increased when communication links are lossy). Secondly, theacknowledgement packets are assumed to be loss-free, but in practicethey are subject to both channel losses and collision losses. Thirdly,channel loss rates and collision loss rates can only be estimated forreceived corrupted packets at the access point, not for packets thatwere transmitted but not received at this access point. Fourthly, it isspecific to the client/access point WLAN environment and exploits aspecial type of feedback from the access point that provides informationon bit errors and symbol errors within a packet.

A second solution of the continuous class is described in the documentof K. Whitehouse et al., “Exploiting the capture effect for collisiondetection and recovery”, EmNetS-11, 2005. This second solution attemptsto detect two types of collisions in the presence of capture in a sensornetwork: stronger-first and stronger-last where the packet with thestronger power comes first and last, respectively. In a stronger-firstcollision the receiver node detects a collision by finding a new extratermination symbol, while in a stronger-last collision the receiver nodedetects a collision by finding a new preamble during the reception ofanother packet.

This second solution has several drawbacks. Firstly, it can be onlyapplied to restricted collision scenarios for successful detection (thetransmissions which result in a collision should have enough differencesin transmission start time and receiving power). Secondly, astronger-last detection requires modifications on the transmitter nodeside (a new extra termination symbol). Thirdly, it requires low-levelaccess to communication parameters which is not provided by mostexisting standards.

A third solution of the continuous class is described in the document ofJ. Yun et al., “Collision detection based on RF energy duration in IEEE802.11 wireless LAN”, Comsware, 2006, New Delhi, India. It aims atdetecting collision in 802.11 WLANs by measuring the RF energy and itschanges during such an event. The main assumption is that the RF energyduration of a collision is greater than the RF energy duration ofindividual transmissions. The access point of a basic service set (BSS)measures RF energy duration on a channel and broadcasts this result toits clients. Then, the clients detect collisions by checking theduration against the duration of their previous transmission schedules.

This third solution has several drawbacks. Firstly, it is specific toWLAN scenarios and requires low-level access and MAC layer modificationswhich are not provided by the 802.11 standard. Secondly, it mayintroduce significant overhead to communicate the RF energy informationfrom an access point back to its clients.

A fourth solution of the continuous class is described in the documentof S. Wong et al., “Robust rate adaptation for 802.11 wirelessnetworks”, ACM Mobicom, 2006, Los Angeles, Calif., and in the documentof J. Kim et al., “CARA: Collision-aware rate adaptation for IEEE 802.11WLANs”, IEEE INFOCOM 2006, Barcelona, Spain. This fourth solution isbased on the use of RTS/CTS MAC layer control messages that precede datatransmissions to detect collisions and perform intelligent data rateadaptation in 802.11 WLANs. Failure of the RTS/CTS packets is attributedto collision because these packets are small and sent at the lowestmodulation data rate, and failure of data packet following a successfulRTS/CTS is attributed to channel loss. To reduce overhead, the RTS/CTSmechanism is enabled adaptively only when collision is detected.

This fourth solution has several drawbacks. Firstly, it is specific to802.11 WLANs and data rate adaptation mechanisms. Secondly, accuratecomputation of collision and channel error rates requires the 802.11RTS/CTS mechanism to be always enabled. However in practice RTS/CTS istypically not enabled due to the high overhead, especially at the highermodulation data rates. Thirdly, it requires modifications of the 802.11MAC protocol which are not supported by the 802.11 standard.

A fifth solution of the continuous class is described in the document ofY. Cheng et al., “Jigsaw: solving the puzzle of enterprise 802.11analysis”, ACM SIGCOMM, 2006, Pisa, Italy, and in the document of R.Mahajan et al., “Analyzing the MAC-level behavior of wireless networksin the wild”, ACM SIGCOMM, 2006, Pisa, Italy. This fifth solution isbased on passive monitoring techniques consisting in computing packetoverlaps using monitor nodes and global network knowledge. Monitor nodesare dedicated hardware devices that “sniff” all packets received aroundthe normal nodes and report them to a central server. The central serveris in charge of computing all timings based on a global reference andthen of determining which packets overlapped in time.

This fifth solution has several drawbacks. Firstly, it introduces animplementation complexity and a communication overhead for communicatingall the information to the central server. Secondly, it requires aglobal up-to-date network knowledge at the central server to perform anaccurate estimation. Even with such global knowledge it is notstraightforward to infer collision loss or channel loss, because packetoverlaps do not always result in collision losses, due to physicalcapture which is difficult to model in general. Thirdly, the predictivepower of a passive monitoring technique heavily depends on how denselythe monitor nodes are deployed, because when the density increases theprobability that a monitor node is close to any given communication linkincreases.

SUMMARY OF THE INVENTION

The objective of this invention is to offer a method and an associateddevice allowing estimation (or computation) of the two components of themeasured packet loss rate, i.e. the channel loss rate and the collisionloss rate, during the operation of a random access network.

More precisely, the invention provides a method, intended for computingchannel loss rate (p_(ch)) and collision loss rate (p_(coll)) of atleast one communication link established between nodes of a networkusing a random access MAC protocol, and comprising the steps of:

-   i) dividing time in probing windows (pw) and transmitting a chosen    number S of probe packets during each probing window (pw) from a    transmitter node to a receiver node linked therebetween,-   ii) measuring a packet loss rate (p) from probe packets lost on this    communication link during a probing window (pw),-   iii) scanning each probing window (pw) with smaller sliding windows    (sw_(i) ^((Wk))), each having a size Wk smaller than S, to identify    the sliding window during which only channel losses occur (estimated    as the sliding window that yields the minimum packet loss rate), and    then computing a channel loss rate (p_(ch)) on this communication    link from this identified sliding window (sw_(i) ^((Wk))), and-   iv) computing a collision loss rate (p_(coll)) on this communication    link by subtracting the channel loss rate (p_(ch)) from the measured    packet loss rate (p).

S being a number (of probe packets) it also defines the size of a windowin terms of number of packets that this window may contain.

The method according to the invention may include additionalcharacteristics considered separately or combined, and notably:

-   -   in step i) the transmitter node may transmit probe packets that        are network layer packets;        -   in step i) the transmitted probe packets can be implemented            either as dedicated control packets or dedicated data that            are inserted inside data packets;    -   in step i) each probing window (pw) may be a time window;        -   in step i) each probe packet to be transmitted during a            probing window (pw) may comprise a bit denoting that it is a            probe packet;    -   in a variant, in step i) each probing window (pw) may be defined        by a sequence number comprised into each of its S associated        probe packets;    -   in step iii) one may scan each probing window (pw) with a step        of one probe packet;    -   in step iii) one may determine a primary packet loss rate (p_(i)        ^((Wk))) for each sliding window (sw_(i) ^((Wk))) of a probing        window (pw) having a size Wk, by dividing the number (n_(i)        ^((Wk))) of probe packets lost during this sliding window        (sw_(i) ^((Wk))) by the size (or number of probes) Wk of this        sliding window (sw_(i) ^((Wk))), then one may reproduce these        determinations for a chosen number of different sizes Wk,        comprised between a minimum size W_(min) and S, then one may        determine a secondary packet loss rate (p^((Wk))) for each of        these different sizes Wk from the associated determined primary        packet loss rates (p_(i) ^((Wk))), then one may determine a size        Wk that provides the best estimate of channel loss rate (p_(ch))        amongst the different sizes Wk;        -   in step iii) one may compare each determined secondary            packet loss rate (p^((Wk))), associated to a size Wk smaller            than or equal to a chosen value, with a variable threshold            depending on the measured packet loss rate (p), then if at            least one of these compared secondary packet loss rates            (p^((Wk))) is greater than this variable threshold, one may            choose S as determined size and then one may assign the            value of the measured packet loss rate (p), corresponding to            the size S, to the channel loss rate (p_(ch)), and if these            compared secondary packet loss rates (p^((Wk))) are smaller            than or equal to this variable threshold, one may            approximate the sequence of determined secondary packet loss            rates (p^((Wk))) by a logarithmic curve of the form a            ln(Wk)+b, then one may determine the point (P_(lc)) of this            logarithmic curve which has the highest curvature, then one            may choose the size Wk which corresponds to this determined            point (P_(lc)) as determined size, and then one may assign            the value of the secondary packet loss rate (p^((Wk))) which            is associated to this determined size Wk to the channel loss            rate (P_(ch));        -   the chosen value may be equal to S/2;        -   the variable threshold may be equal to (1−ε)·p, where ε is a            chosen parameter greater than 0 and smaller than 1. For            instance, ε may be chosen into the interval [0.005, 0.015];        -   each secondary packet loss rate (p^((Wk))), associated to            one of the different sizes Wk, may be the minimum of the            primary packet loss rates (p_(i) ^((Wk))) that have been            determined for this size Wk;        -   the minimum size W_(min) may correspond to the coarsest            estimation of channel loss rate. It may either be provided            as a requirement or depend on network properties such as the            maximum transmission rate of probe packets.

The invention also provides a device, intended for computing onlinechannel loss rate (p_(ch)) and collision loss rate (p_(coll)) of atleast one communication link established between nodes of a networkusing a random access MAC protocol, and comprising:

-   -   a measurement means arranged for measuring a packet loss        rate (p) from probe packets lost on this communication link        during a probing window (pw) during which S probe packets are        transmitted on this communication link from a transmitter node        to a receiver node,    -   a first computation means arranged for scanning each probing        window (pw) with smaller sliding windows (sw_(i) ^((Wk))), each        having a size Wk smaller than S, to identify the sliding window        during which only channel losses occur (estimated as the sliding        window that yields the minimum packet loss rate), and then for        computing a channel loss rate (p_(ch)) on this communication        link from this identified sliding window (sw_(i) ^((Wk))),    -   a second computation means (CM2) arranged for computing a        collision loss rate (p_(coll)) on this communication link by        subtracting the computed channel loss rate (p_(ch)) from the        measured packet loss rate (p).

This first computation means may be further arranged:

-   -   for determining a primary packet loss rate (p_(i) ^((Wk))) for        each sliding window (sw_(i) ^((Wk))) of a probing window (pw)        having a size Wk, by dividing the number (n_(i) ^((Wk))) of        probe packets lost during this sliding window (sw_(i) ^((Wk)))        by the size Wk of this sliding window (sw_(i) ^((Wk))), then    -   for reproducing these determinations for a chosen number of        different sizes Wk, comprised between a minimum size W_(min) and        S, then    -   for determining a secondary packet loss rate (p^((Wk))) for each        of the different sizes Wk from the associated determined primary        packet loss rates (p_(i) ^((Wk))), then    -   for determining a size Wk that provides the best estimate of        channel loss rate (p_(ch)) amongst the different sizes Wk.

This first computation means may be still further arranged:

-   -   for comparing each determined secondary packet loss rate        (p^((Wk))), associated to a size Wk smaller than or equal to a        chosen value, with a variable threshold depending on the        measured packet loss rate (p), then    -   if at least one of these compared secondary packet loss rates        (p^((Wk))) is greater than this variable threshold, for choosing        S as determined size and then for assigning the value of the        measured packet loss rate (p), corresponding to size S, to the        channel loss rate (p_(ch)), and if these compared secondary        packet loss rates (p^((Wk))) are smaller than or equal to the        variable threshold, for approximating the sequence of determined        secondary packet loss rates (p^((Wk))) by a logarithmic curve of        the form a ln(Wk)+b, then for determining the point (P_(lc)) of        this logarithmic curve which has the highest curvature, then for        choosing the size Wk which corresponds to this determined point        (P_(lc)) as determined size, and then for assigning the value of        the secondary packet loss rate (p^((Wk))) which is associated to        this determined size Wk to the channel loss rate (p_(ch)).

This first computation means may be still further arranged fordetermining each secondary packet loss rate (p^((Wk))), associated toone of the different sizes Wk, from the minimum of the primary packetloss rates (p_(i) ^((Wk))) that have been determined for this size Wk.

The invention also provides a (communication) node, intended forcommunicating into a network using a random access MAC protocol, andcomprising a device such as the one above introduced.

BRIEF DESCRIPTION OF THE FIGURE

Other features and advantages of the invention will become apparent onexamining the detailed specifications hereafter and the appendeddrawing, wherein the unique FIGURE schematically and functionallyillustrates an example of network comprising four communicationequipments (or nodes) linked therebetween and each equipped with anexample of embodiment of a device according to the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

The appended drawing may serve not only to complete the invention, butalso to contribute to its definition, if need be.

The invention aims at offering a method, and an associated device (D),intended for computing online the two components (channel loss rate andcollision loss rate) of a packet loss rate measured on at least onecommunication link established between two nodes (Nj) of a random accessnetwork (WN) (i.e. a network using a random access MAC protocol).

In the following description it will be considered that the network (WN)is of the wireless type, and more precisely that it is an IEEE 802.11network (for instance a WiFi network). But the invention is not limitedto this type of network. Indeed it concerns any type of networkcomprising nodes (or network equipments) using a random access MACprotocol. So it may be also a wireline network using a random access MACprotocol like Ethernet.

Moreover, the invention concerns not only networks of the multi-hop type(i.e. comprising routers or access points (APs) connected (or linked)therebetween), but also networks of the single-hop type (i.e. comprisingbase stations (or any equivalent radio network equipments) serving user(or client) wireless communication equipments). It is recalled that asingle-hop type wireless network is a particular case of a multi-hoptype wireless network.

In the illustrated example the nodes Nj are either access points of thenetwork WN or mobile phones of users that are connected to the networkWN through its access points. More generally a node can be either anetwork equipment (such as a router or an access point) or a usercommunication equipment (such as a mobile phone, a personal digitalassistant (or PDA), a fixed computer or a laptop).

Moreover, in the illustrated example the node index j varies from 1 to4, but the number of nodes Nj may be greater or smaller than 4.

As mentioned before, the invention proposes a method intended forcomputing online the channel loss rate and collision loss rate of atleast one communication link established between two nodes Nj and Nj′(with j≠j′) of a (random access) network WN.

This method is based on the assumptions that (i) collision losses areindependent from channel losses, and therefore packet loss increases dueto collisions, (ii) interference and collisions create bursty losspatterns, and (iii) losses occur independently when collisions are notpresent.

Such a method can be implemented at least partly by at least one deviceD according to the invention.

As it is schematically illustrated in the unique FIGURE, a device D,according to the invention, may be located into several (and preferablyeach) node Nj of the network WN. But this device D could be also anetwork equipment or element coupled to a node Nj, or a networkequipment connected to the network WN, such as a management equipment.

So, a device D can be made of software modules, at least partly, or ofelectronic circuit(s) or hardware modules, or else of a combination ofhardware and software modules (in this case the device D comprises alsoa software interface allowing interworking between the hardware andsoftware modules).

When devices D are distributed into the nodes Nj, each of them makescomputation for its node Nj. When there is only one device D for thewhole network or for a part of a network, this centralized device Dmakes computations for all the nodes Nj or for the nodes Nj belonging toits network part.

The method according to the invention comprises four main steps.

The first main step (i) of the method consists in dividing time inprobing windows pw and in transmitting a chosen number S of probepackets during each probing window pw from a transmitter node Nj (forinstance N1) to a receiver node Nj′ (for instance N2) which are linkedtherebetween.

It is important to note that when two nodes Nj are linked therebetweenand both equipped with a device D they both transmit each other the samenumber S of probe packets during probing windows pw of the same size. Sis a tunable parameter known to both transmitter node and receiver nodeof each pair of linked nodes.

For instance in an IEEE 802.11g wireless mesh network, the number S ofprobe packets transmitted during each probing windows pw may range from200 to 1280, and the duration of each probing windows pw may range from2 minutes to 15 minutes.

This first main step (i) can be implemented by each node Nj possiblyunder control of its associated device D.

The probing window pw can be implemented either as a time window, or byusing sequence numbers in the probe packets.

The probe packets are preferably network layer packets. The transmittedprobe packets can be implemented either as dedicated control packets ordedicated data that are inserted inside data packets that the nodes Njof a pair exchange therebetween. Moreover, in the MAC layer the probepackets can be mapped either to broadcast or unicast transmissions.

The information carried in (and/or defining) probe packets depends onthe implementation of the probing window pw. If the probing window pw isimplemented as a time window, then each probe packet comprises at leastone bit denoting that it is a probe packet. If the probing window pw isdefined by a sequence number, then each probe packet transmitted duringa probing window pw comprises one or more bits defining the sequencenumber of its probing window pw, and also possibly one bit denoting thatit is a probe packet.

The second main step (ii) of the method consists in measuring the packetloss rate p from the probe packets that are lost on a consideredcommunication link during a probing window pw.

The packet loss rate p measured during a probing window pw is equal tothe ratio between the number of probe packets that have been effectively(and correctly) received by a receiver node Nj′ during this probingwindow pw and the number S of probe packets sent during this probingwindow pw by the transmitter node Nj.

This second main step (ii) can be implemented by a measurement means (ormodule) MM of a device D, from information relative to the receivedprobe packets provided by its associated receiver node Nj′.

The third main step (iii) of the method consists in scanning eachprobing window pw with smaller sliding windows sw_(i) ^((Wk)), eachhaving a size Wk which is smaller than S (i.e. the size of the probingwindow pw), in order to identify the sliding window during which onlychannel losses occur (i.e. estimated as the sliding window that yieldsthe minimum packet loss rate). Then one computes a channel loss ratep_(ch), on this communication link from this identified sliding windowsw_(i) ^((Wk)).

The sliding window index i varies from 1 to M, where M (number ofsliding windows sw_(i) ^((Wk)) contained into a probing window pw)depends on the size Wk of these sliding windows sw_(i) ^((Wk)).

This third main step (iii) can be implemented by a first computationmeans (or module) CM1 of a device D, which is coupled to its measurementmeans MM.

For instance, one (CM1) may scan each probing window pw with a step ofone probe packet. This provides S−Wk+1 starting positions, each startingposition corresponding to the start of a sliding window sw_(i) ^((Wk))within the probing window pw.

The sliding window identification can be carried out as follows.

For instance, one (CM1) may start by determining a primary packet lossrate p_(i) ^((Wk)) for each sliding window sw_(i) ^((Wk)) of a probingwindow pw having a size Wk. This can be done by dividing the numbern_(i) ^((Wk)) of probe packets that have been lost during this slidingwindow sw_(i) ^((Wk)), due to channel errors, by the size Wk of thissliding window sw_(i) ^((Wk)) (i.e. p_(i) ^((Wk))=n_(i) ^((Wk))/Wk).

Then one (CM1) reproduces the determination of primary packet loss ratesp_(i) ^((Wk)) for a chosen number N of different sizes Wk. Thesedifferent sizes are comprised between a minimum size W_(min) and S. Inother words, one (CM1) determines N groups of primary packet loss ratesp_(i) ^((Wk)) for N different sizes Wk.

For instance, the minimum size W_(min) corresponds to the coarsestestimation of channel loss rate supported by the network WN. Forinstance, a minimum size W_(min) equal to 10 (i.e. equal to 10 samples)corresponds to 11 loss rates, ranging from zero to 1.0, with a step of0.1.

Then one (CM1) may determine a secondary packet loss rate p^((Wk)) foreach of the N different sizes Wk from the associated group of primarypacket loss rates p_(i) ^((Wk)).

For instance, each secondary packet loss rate p^((Wk)), associated toone of the N different sizes Wk, is estimated as the minimum of theprimary packet loss rates p_(i) ^((Wk)) that have been determined forits associated size Wk:

$\begin{matrix}{p^{({Wk})} = {\min\left( {p_{1}^{({Wk})},p_{2}^{Wk},\ldots\mspace{14mu},p_{S - {Wk} + 1}^{Wk}} \right)}} \\{{= {\frac{1}{Wk}{\min\left( {n_{1}^{({Wk})},n_{2}^{({Wk})},\ldots\mspace{14mu},n_{S - {Wk} + 1}^{({Wk})}} \right)}}},}\end{matrix}$ with  Wk ∈ [W_(min), …  , S].

Once N secondary packet loss rates p^((Wk)) have been estimated for theN different sizes Wk, respectively, one (CM1) may determine the size Wkwhich provides the best estimate of channel loss rate p_(ch) amongstthese N different sizes Wk.

This size determination aims at identifying sliding window(s) sw_(i)^((Wk)) during which only channel losses occur. Indeed, one can showthat there are periods without collisions that are long enough to beused to measure only the channel loss rate p_(ch). So, once such periodshave been identified, one has to determine the size Wk which is largeenough to give a good estimate of p_(ch), but not so large that onewould finally end-up into a period of collision losses.

If one decides to choose the largest size S as determined size Wk, itwill provide only one sample which is the measured packet loss rate pthat includes both collision and channel losses. Hence, such a choice ofdetermined size Wk cannot discriminate between the two types of lossesand therefore over-estimate the channel losses.

Now, if one decides to choose a very small size as determined size Wk,one may capture very few losses (the “min” operator in the precedingequation giving p_(i) ^((Wk)) will yield 0 if losses are rare enough),and therefore this will under-estimate the channel error rate p_(ch).For small sizes Wk, the estimate of secondary packet loss rate p^((Wk))is smaller than p because some windows see too few losses (because theyare not long enough to accurately “average out” the channel losses).Then p^((Wk)) increases with the size Wk until it reaches the measuredpacket loss for Wk=S(p^((Wk=s))=p).

So based on these observations, one proposes hereafter an example ofsize determination (or filter) which offers good results.

For instance, one (CM1) may first select each estimated (or determined)secondary packet loss rate p^((Wk)) which is associated to a size Wksmaller than or equal to a chosen value. For instance, this chosen valuemay be equal to S/2.

Then one (CM1) may compare each of these selected secondary packet lossrate p^((Wk)) with a variable threshold. The latter may depend on themeasured packet loss rate p (obtained during the second main step (ii)),for instance. Such a variable threshold may be equal to (1−ε)·p, where εis a chosen parameter which is greater than 0 and smaller than 1 (εε]0,1[), for instance. More preferably ε may be chosen into the interval[0.005, 0.015]. For instance it may be equal to 0.01 (or 1%).

If at least one of the compared secondary packet loss rates p^((Wk)) isgreater than the variable threshold, this means that p^((Wk)) increasessteeply and reaches p fast, which is a strong indication that thechannel loss rate p_(ch) is close to the measured packet loss rate p.So, one (CM1) may choose S as determined size, and therefore one (CM1)may assign the value of the measured packet loss rate p (whichcorresponds to this size S) to the channel loss rate p_(ch).

Now, if all the compared secondary packet loss rates (p^((Wk))) aresmaller than or equal to the variable threshold, one (CM1) mayapproximate the sequence of determined secondary packet loss rates(p^((Wk))) by a logarithmic curve of the form a ln(Wk)+b, for instance.Then one (CM1) may determine the point P_(lc) of this logarithmic curvewhich has the highest curvature and then the size Wk* which correspondsto this determined point P_(lc).

So, one (CM1) may choose the size Wk* (which corresponds to thedetermined point P_(lc)) as determined size, and one (CM1) may assignthe value of the secondary packet loss rate p^((Wk)*⁾ (which isassociated to this determined size Wk*) to the channel loss rate p_(ch)(i.e. p_(ch)=p^((Wk)*⁾). The point of highest curvature is awell-defined point where the function p^((Wk)*⁾ increases steeply andreaches p fast, which is a strong indication that the channel loss ratep_(ch) is close to the measured packet loss rate p.

The fourth main step (iv) of the method consists in computing thecollision loss rate p_(coll) on the considered communication link bysubtracting the computed (or estimated) channel loss rate p_(ch) fromthe measured packet loss rate p (i.e. p_(coll)=p−p_(ch)).

This fourth main step (iv) can be implemented by a second computationmeans (or module) CM2 of a device D, which is coupled to its measurementmeans MM and to the first computation means (or module) CM1.

The invention does not only apply to a single communication link, asdescribed above. Indeed it may also applied simultaneously to several(even all the) communication links of a random access network, where theendpoint nodes of each communication link (or there associated devicesD) execute the transmitter actions (sending probe packets) and thereceiver actions (computing the channel loss rate and collision lossrate) as described above. Furthermore, in a wireless network theinvention can be implemented with broadcast probes. In this case, itwill require O(N) measurements to compute the channel loss rates andcollision loss rates for all communication links in this wirelessnetwork.

The invention being based on statistical properties of packet receptiontimings at the network layer, it offers several advantages, amongstwhich:

-   -   it does not require suspension of network operation for        collection of measurements,    -   it is independent of the network technology, and therefore can        operate over any random access network (it can be applied to        multi-hop and single-hop networks),    -   it requires no low-level information or MAC layer modifications        to existing network standards,    -   the overhead it causes is relatively small and can be controlled        by adjusting the parameter S of the probing window. Typically,        probing is performed at the network layer by sending probe        packets every few seconds,    -   it can be applied to numerous applications, and notably to        capacity estimation, traffic/topology optimizations, admission        control and efficient design of data rate adaptation mechanisms        in random access networks.

The invention is not limited to the embodiments of method, device andnode (or communication equipment) described above, only as examples, butit encompasses all alternative embodiments which may be considered byone skilled in the art within the scope of the claims hereafter.

The invention claimed is:
 1. Method for computing online channel lossrate of at least one communication link established between nodes of anetwork using a random access MAC protocol, wherein it comprises thesteps of: i) dividing time in probing windows and transmitting a chosennumber S of probe packets during each probing window from a transmitternode to a receiver node linked therebetween, ii) measuring a packet lossrate from probe packets lost on said communication link during a probingwindow, iii) scanning each probing window with smaller sliding windows,each having a size Wk smaller than S, to identify the sliding windowduring which only channel losses occur, and then for computing a channelloss rate on this communication link from this identified slidingwindow.
 2. Method according to claim 1, wherein it comprises the furtherstep of: iv) computing a collision loss rate on said communication linkby subtracting said computed channel loss rate from said measured packetloss rate.
 3. Method according to claim 1 wherein in step i) saidtransmitter node transmits probe packets that are network layer packets.4. Method according to claim 3, wherein in step i) said transmittedprobe packets are implemented either as dedicated control packets ordedicated data that are inserted inside data packets.
 5. Methodaccording to claim 1, wherein in step i) each probing window is a timewindow.
 6. Method according to claim 5, wherein in step i) each probepacket to be transmitted during a probing window comprises a bitdenoting that it is a probe packet.
 7. Method according to claim 1wherein in step i) each probing window) is defined by a sequence numbercomprised into each of its S associated probe packets.
 8. Methodaccording to claim 1, wherein in step iii) one scans each probing windowwith a step of one probe packet using smaller sliding windows.
 9. Methodaccording to claim 1 wherein in step iii) one determines a primarypacket loss rate) for each sliding window of a probing window having asize Wk by dividing the number of probe packets lost during said slidingwindow by said size Wk of said sliding window, then one reproduces thesedeterminations for a chosen number of different sizes Wk, comprisedbetween a minimum size W_(min) and S, then one determines a secondarypacket loss rate for each of said different sizes Wk from the associateddetermined primary packet loss rates, then one determines a size Wk thatprovides the best estimate of channel loss rate amongst said differentsizes Wk.
 10. Method according to claim 9, wherein said variablethreshold is equal to (1−ε)·p, where ε is a chosen parameter greaterthan 0 and smaller than
 1. 11. Device for computing online channel lossrate of at least one communication link established between nodes of anetwork using a random access MAC protocol, wherein it comprises: ameasurement means arranged for measuring a packet loss rate from probepackets lost on said communication link during a probing window duringwhich S probe packets are transmitted on said communication link from atransmitter node to a receiver node, a first computation means arrangedfor scanning each probing window with smaller sliding windows, eachhaving a size Wk smaller than S, to identify the sliding window duringwhich only channel losses occur, and then for computing a channel lossrate on this communication link from this identified sliding window(sw_(i) ^((Wk))).
 12. Device according to claim 11, wherein it furthercomprises a second computation means arranged for computing a collisionloss rate on said communication link by subtracting said computedchannel loss rate from said measured packet loss rate.
 13. Deviceaccording to claim 11, wherein it carries out a method.
 14. Deviceaccording to claim 11, wherein said first computation means is arranged:i) for determining a primary packet loss rate for each sliding window ofa probing window having a size Wk by dividing the number of probepackets lost during said sliding window by said size Wk of said slidingwindow, then ii) for reproducing these determinations for a chosennumber of different sizes Wk, comprised between a minimum size W_(min)and S, then iii) for determining a secondary packet loss rate for eachof said different sizes Wk from the associated determined primary packetloss rates, then iv) for determining a size Wk that provides the bestestimate of channel loss rate amongst said different sizes Wk.
 15. Nodeintended for communicating into a network using a random access MACprotocol, wherein it comprises a device according to claim 11.